astra <- read.csv("https://raw.githubusercontent.com/QMSS-G5063-2023/course_content/main/Exercises/03_astronauts%20-%20GRADED/astronauts.csv?token=GHSAT0AAAAAAB557SY67DYJGWWUEAM4MRUIY7M3XOA")
head(astra)

##   id number nationwide_number                name
## 1  1      1                 1       Gagarin, Yuri
## 2  2      2                 2      Titov, Gherman
## 3  3      3                 1 Glenn, John H., Jr.
## 4  4      3                 1 Glenn, John H., Jr.
## 5  5      4                 2 Carpenter, M. Scott
## 6  6      5                 2 Nikolayev, Andriyan
##                                            original_name  sex year_of_birth
## 1           Ð“Ð\220Ð“Ð\220Ð Ð\230Ð\235 Ð®Ñ\200Ð¸Ð¹ Ð\220Ð»ÐµÐºÑ\201ÐµÐµÐ²Ð¸Ñ‡ male          1934
## 2           Ð¢Ð\230Ð¢ÐžÐ’ Ð“ÐµÑ\200Ð¼Ð°Ð½ Ð¡Ñ‚ÐµÐ¿Ð°Ð½Ð¾Ð²Ð¸Ñ‡ male          1935
## 3                                    Glenn, John H., Jr. male          1921
## 4                                    Glenn, John H., Jr. male          1921
## 5                                    Carpenter, M. Scott male          1925
## 6 Ð\235Ð\230ÐšÐžÐ›Ð\220Ð•Ð’ Ð\220Ð½Ð´Ñ\200Ð¸Ñ\217Ð½ Ð“Ñ\200Ð¸Ð³Ð¾Ñ\200ÑŒÐµÐ²Ð¸Ñ‡ male          1929
##      nationality military_civilian              selection year_of_selection
## 1 U.S.S.R/Russia          military                 TsPK-1              1960
## 2 U.S.S.R/Russia          military                 TsPK-1              1960
## 3           U.S.          military NASA Astronaut Group 1              1959
## 4           U.S.          military NASA Astronaut Group 2              1959
## 5           U.S.          military                NASA- 1              1959
## 6 U.S.S.R/Russia          military                 TsPK-1              1960
##   mission_number total_number_of_missions occupation year_of_mission
## 1              1                        1      pilot            1961
## 2              1                        1      pilot            1961
## 3              1                        2      pilot            1962
## 4              2                        2        PSP            1998
## 5              1                        1      Pilot            1962
## 6              1                        2      pilot            1962
##     mission_title  ascend_shuttle        in_orbit descend_shuttle hours_mission
## 1        Vostok 1        Vostok 1        Vostok 2        Vostok 3          1.77
## 2        Vostok 2        Vostok 2        Vostok 2        Vostok 2         25.00
## 3            MA-6            MA-6            MA-6            MA-6          5.00
## 4          STS-95          STS-95          STS-95          STS-95        213.00
## 5 Mercury-Atlas 7 Mercury-Atlas 7 Mercury-Atlas 7 Mercury-Atlas 7          5.00
## 6        Vostok 3        Vostok 3        Vostok 3        Vostok 3         94.00
##   total_hrs_sum eva_instances eva_hrs_mission total_eva_hrs
## 1          1.77             0               0             0
## 2         25.30             0               0             0
## 3        218.00             0               0             0
## 4        218.00             0               0             0
## 5          5.00             0               0             0
## 6        519.33             0               0             0

Age & Sex

astra$age_of_selection <- astra$year_of_selection - astra$year_of_birth

library(ggplot2)

## Warning: package 'ggplot2' was built under R version 4.1.3

# Scatter plot
ggplot(astra, aes(x = year_of_birth, y = age_of_selection, color=sex)) +
  geom_point(alpha=0.5) +
  labs(x="Year of Birth", y="Age of Selection", color="sex") +
    theme(legend.position="right") +
  ggtitle("Age of selection by years of birth: gender difference")

# Few female pilots
# Female astraunauts began to be selected from 1940's birth cohort
# Age range differ by gender

# Box plot (show age distribution for each birth cohort, by gender)
astra <- within(astra, {
  birth_cohort <- NA
  birth_cohort[year_of_birth<1930] <- "Before 1920's"
  birth_cohort[year_of_birth>=1930 & year_of_birth <1940] <- "1930's"
  birth_cohort[year_of_birth>=1940 & year_of_birth < 1950] <- "1940's"
  birth_cohort[year_of_birth>=1950 & year_of_birth < 1960] <- "1950's"
  birth_cohort[year_of_birth>=1960 & year_of_birth < 1970] <- "1960's"
  birth_cohort[year_of_birth>=1970 ] <- "1970's and after"
})

ggplot(astra, aes(x=reorder(birth_cohort, year_of_birth, na.ra=TRUE), y=age_of_selection)) +
  geom_boxplot(aes(fill=sex), outlier.colour = "transparent",
               alpha = 0.3) + #<< fill in different colors by "sex" 
  coord_flip() + labs(x="Year of Birth", y="Age of Selection") +
    theme(legend.position="right") +
    ggtitle("Age of selection by birth cohorts: gender difference")

# Few female pilots
# Female astraunauts began to be selected not until 1940's birth cohort
# Age range differ by gender

ggplot(astra, aes(x=reorder(birth_cohort, year_of_birth, na.ra=TRUE), y=age_of_selection)) +
  geom_jitter(shape=21, aes(fill=sex), color="transparent",
              position = position_jitter(w=0.1)) +
  coord_flip() + labs(x="", y="age of selection") +
    theme(legend.position="right") +
    ggtitle("Age of selection by years of birth: gender difference")

# Few female pilots
# Female astraunauts began to be selected from 1940's birth cohort
# Age range differ by gender

The scatter chart and the jitter chart both shows that (1) there are fewer female astranauts, (2) female astranauts took part in the space mission beginning from 1930’s birth cohort, and (3) the age range is more restrictive for females.
I would recommend to use the jitter chart because it shows the gender and age distribution of the astraunauts by birth cohorts more intuitively.
I considered the principles of similarities (using consistent color for all male and female) and proximity (used the distance between data points to group/distinguish birth cohorts). I tried to make the graph simple by not adding box plot to the graph since the proximity of data points show the age range.

Nationality

require(dplyr)

## Loading required package: dplyr

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

astra <- astra %>%
  group_by(nationality) %>%
  mutate(year_of_first_mission = min(year_of_mission))

astra <- astra %>%
  group_by(mission_title) %>%
  mutate(joint_mission = as.integer(n_distinct(nationality) > 1))

summarize(astra, id, nationality, year_of_first_mission, mission_title, joint_mission, eva_instances, eva_hrs_mission, total_eva_hrs)

## `summarise()` has grouped output by 'mission_title'. You can override using the
## `.groups` argument.

## # A tibble: 1,277 x 8
## # Groups:   mission_title [362]
##    mission_title    id nationality  year_of_first_m~ joint_mission eva_instances
##    <chr>         <int> <chr>                   <int>         <int>         <int>
##  1 1               205 U.S.S.R/Rus~             1961             1             2
##  2 1               284 U.S.S.R/Rus~             1961             1             2
##  3 1               434 U.S.S.R/Rus~             1961             1             0
##  4 1               438 Syria                    1987             1             0
##  5 1               455 U.S.S.R/Rus~             1961             1             0
##  6 1               462 U.S.                     1962             1             0
##  7 1               815 U.S.S.R/Rus~             1961             1             0
##  8 10              386 U.S.S.R/Rus~             1961             1             1
##  9 10              587 U.S.S.R/Rus~             1961             1             0
## 10 10              758 U.S.                     1962             1             2
## # ... with 1,267 more rows, and 2 more variables: eva_hrs_mission <dbl>,
## #   total_eva_hrs <dbl>

ggplot(astra, aes(x = reorder(nationality, -year_of_first_mission), y = year_of_mission, color=joint_mission)) +
  geom_point(alpha=0.5) +
  coord_flip() +
  labs(x="", y="Year of missions", color="joint mission") +
    theme(legend.position="right") +
    ggtitle("World-wide history of space missions: astronauts across countries")

Dot plot is used to map the year of missions for each country in a simple manner. The countries are aligned by the first year of mission to show that countries other than the U.S. or Russia gradually to join the space mission. Also, this graph shows the frequency of the joint mission, the shuttle mission that astranauts with mix of countries participated in.

Space walks

library(dplyr)
agg <- astra %>%
  group_by(name) %>%
  summarize('num_of_eva'=sum(eva_instances),
            'total_eva'=sum(total_eva_hrs))
summarize(agg, name, num_of_eva, total_eva)

## # A tibble: 564 x 3
##    name                             num_of_eva total_eva
##    <chr>                                 <int>     <dbl>
##  1 Acaba, Joseph M.                          3      59.8
##  2 Acton, Loren Wilbur                       0       0  
##  3 Adamson, James C.                         0       0  
##  4 Afanasyev, Viktor Mikhaylovich            7     152. 
##  5 Aidyn (Aydyn) Akanovich Aimbetov          0       0  
##  6 Akers, Thomas D.                          4     121. 
##  7 Akiyama, Toyohiro                         0       0  
##  8 Aksyonov, Vladimir                        0       0  
##  9 Al-saud, Sultan bin Salman                0       0  
## 10 Al Mansoori, Hazzaa                       0       0  
## # ... with 554 more rows

library(ggthemes)

## Warning: package 'ggthemes' was built under R version 4.1.3

dplot <- ggplot(agg, aes(x=num_of_eva, y=total_eva)) +
        geom_bar(stat="summary", fill="steelblue")+
  labs(x="The number of EVA", y="Total hours of EVA")+
    ggtitle("The relationship between the number of EVA and total hours of EVA")
dplot

## No summary function supplied, defaulting to `mean_se()`

Choose my own: trends in hours of space missions over time (1960-2020)

# Whether the mission lasted over 30 days
astra$success <- as.numeric(astra$hours_mission > 720)
head(astra)

## # A tibble: 6 x 29
## # Groups:   mission_title [6]
##      id number nationwide_number name          original_name sex   year_of_birth
##   <int>  <int>             <int> <chr>         <chr>         <chr>         <int>
## 1     1      1                 1 Gagarin, Yuri "Ð“Ð\u0090Ð“~ male           1934
## 2     2      2                 2 Titov, Gherm~ "Ð¢Ð˜Ð¢ÐžÐ’ ~ male           1935
## 3     3      3                 1 Glenn, John ~ "Glenn, John~ male           1921
## 4     4      3                 1 Glenn, John ~ "Glenn, John~ male           1921
## 5     5      4                 2 Carpenter, M~ "Carpenter, ~ male           1925
## 6     6      5                 2 Nikolayev, A~ "Ð\u009dÐ˜Ðš~ male           1929
## # ... with 22 more variables: nationality <chr>, military_civilian <chr>,
## #   selection <chr>, year_of_selection <int>, mission_number <int>,
## #   total_number_of_missions <int>, occupation <chr>, year_of_mission <int>,
## #   mission_title <chr>, ascend_shuttle <chr>, in_orbit <chr>,
## #   descend_shuttle <chr>, hours_mission <dbl>, total_hrs_sum <dbl>,
## #   eva_instances <int>, eva_hrs_mission <dbl>, total_eva_hrs <dbl>,
## #   age_of_selection <int>, birth_cohort <chr>, ...

astra$yearbin <- cut(astra$year_of_mission,
                     breaks = c(1910, 1920, 1930, 1940, 1950, 1960, 1970, 1980, 1990, 2000, 2010, 2020),
                     labels = c('1910s', '1920s', '1930s', '1940s', '1950s', '1960s', '1970s', '1980s', '1990s', '2000s', '2010s'))

bargraph <- ggplot(astra, aes(x=yearbin, y=success, color = sex))+
  geom_bar(stat = "summary", fun = "mean", fill = "grey", position="dodge") +
  labs(x="", y="% of mission lasted over 30 days")
bargraph

missionhrs <- astra %>%
  group_by(year_of_mission, sex) %>%
  summarize('avghours_mission'=mean(hours_mission),
            'minhours_mission'=min(hours_mission), 
            'maxhours_mission'=max(hours_mission), na.ra=T)

## `summarise()` has grouped output by 'year_of_mission'. You can override using
## the `.groups` argument.

dotlineplot <- ggplot(missionhrs, aes(x=year_of_mission, y=avghours_mission, color = sex))+
  geom_line() + geom_point(size=3) +
  labs(x="", y="Average hours of space missions") +
    ggtitle("Average hours of space missions over time (1960-2020)")
dotlineplot

* The bar graph charts how the percentage of missions whose duration lasted over 30 days(700 hours) changed over every decades, by sex of the astranauts who participated in the missions. The dotted line graph also shows the annual trend of average hours of space missions by sex. Both graphs reveals the interesting pattern that 1) the duration of missions increased over time, particularly in the last decade, and 2) the gender difference in the duration of mission disappeared, and even got reversed in 2010’s. I recommend the dotted line chart as it represents the overall time trends and changes in gender difference more intuitively.

5. Interactivity: make two plots interactive

library(plotly)

## Warning: package 'plotly' was built under R version 4.1.3

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

dotlineplot2 <- ggplot(missionhrs, aes(x=year_of_mission, y=avghours_mission, color = sex, label = minhours_mission))+
  geom_line() + geom_point(size=3) +
  labs(x="", y="Average hours of space missions") +
  ggtitle("Trend in average hourse of space mission")
ggplotly(dotlineplot2,
         tooltip = c("year_of_mission", "avghours_mission", "minhours_mission"))

boxplot <- plot_ly(astra, y=~age_of_selection, x =~reorder(birth_cohort, year_of_birth), color = ~sex, type = "box")
m <- list(l = 100, r = 100, b = 100, t = 10, pad = 10) #<<
boxplot <- boxplot %>% layout(autosize = F, width = 900, height = 400,
                              boxmode="group", 
                              margin = m,
                              yaxis = list(title = "Age of Selection", showticklabels =T),
                              xaxis = list(title = "Birth cohort"),
                              title = 'Age of selection by birth cohorts'
                              )

## Warning: Specifying width/height in layout() is now deprecated.
## Please specify in ggplotly() or plot_ly()

boxplot

## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels

## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels

## Warning: 'layout' objects don't have these attributes: 'boxmode'
## Valid attributes include:
## '_deprecated', 'activeshape', 'annotations', 'autosize', 'autotypenumbers', 'calendar', 'clickmode', 'coloraxis', 'colorscale', 'colorway', 'computed', 'datarevision', 'dragmode', 'editrevision', 'editType', 'font', 'geo', 'grid', 'height', 'hidesources', 'hoverdistance', 'hoverlabel', 'hovermode', 'images', 'legend', 'mapbox', 'margin', 'meta', 'metasrc', 'modebar', 'newshape', 'paper_bgcolor', 'plot_bgcolor', 'polar', 'scene', 'selectdirection', 'selectionrevision', 'separators', 'shapes', 'showlegend', 'sliders', 'smith', 'spikedistance', 'template', 'ternary', 'title', 'transition', 'uirevision', 'uniformtext', 'updatemenus', 'width', 'xaxis', 'yaxis', 'barmode', 'bargap', 'mapType'

6. Data Table

astronaut <- astra %>%
  group_by(name) %>%
  summarize('total_number_of_missions'=max(total_number_of_missions),
            'total_hours_mission'=max(total_hrs_sum),
            'total_eva_hrs'=max(total_eva_hrs))

library("DT")

## Warning: package 'DT' was built under R version 4.1.3

# Fixing Column Labels

library(stringr)
pretty_headers <- 
  gsub("[.]", " ", colnames(astronaut)) %>%
  str_to_title()

# Adding Selection Fields and Sliders
astronaut %>%
  datatable(
    rownames = FALSE,
    colnames = pretty_headers,
    filter = list(position = "top"),
    options = list(
      dom = "Bfrtip",
      buttons = I("colvis"),
      language = list(sSearch = "Filter:")
    ),
    extensions = c("Buttons", "Responsive")
  )

I want to highlight the key achievements of each astronauts: total number of missions, total hours of mission, and total EVA hours. Each record represents different aspects of achiments as an astronaut. The number of missions show the activity, total hours of mission shows the time spent in space, and total EVA hours marks the quality of the missions.

Assignment1_Astraunauts

Eunho Cha

2023-02-09

5. Interactivity: make two plots interactive

6. Data Table